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Morning Edition · Saturday, July 11, 2026Published at 1:46 AM EDT · New York
Anthropic's GRAM Isolates Dual-Use Knowledge Into Removable Modules That Can Be Deleted After Training
In tests across virology, cybersecurity, nuclear physics, and a niche programming language, deleting a module erased the capability as cleanly as never training on the data, without degrading general performance.
Anthropic, working with the applied research firm AE Studio, published GRAM, short for Gradient-Routed Auxiliary Modules, a pretraining method that gives a model dedicated, removable compartments for each category of dual-use knowledge. GRA…
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